COGNITIVE MODELING SYSTEM INCLUDING REPEAT PROCESSING ELEMENTS AND ON-DEMAND ELEMENTS
The present design is directed to a system for performing cognitive modeling, including an event acquirer configured to acquire an event comprising an associated date and set of data fields, an analyzer element comprising a plurality of components repeated for each field in an event received from the event acquirer, wherein the analyzer element applies thresholds to each event, determines outliers, evaluates time-ordered behavior, and predicts threshold violations for the event, a periodic set of components configured to operate periodically on demand, the periodic set of components configured to perform peer to peer analysis, actor correlation analysis, actor behavior analysis, semantic rule analysis, and predict rates of change, and a plurality of signal managers interfacing with the analyzer element and the periodic set of components configured to exclude signals based on content properties of data transmitted.
1 . A system for performing cognitive modeling, comprising:
an event acquirer configured to acquire an event comprising an associated date and set of data fields;
an analyzer element comprising a plurality of components repeated for each field in an event received from the event acquirer, wherein the analyzer element applies thresholds to each event, determines outliers, evaluates time-ordered behavior, and predicts threshold violations for the event;
a periodic set of components configured to operate periodically on demand, the periodic set of components configured to perform peer to peer analysis, actor correlation analysis, actor behavior analysis, semantic rule analysis, and predict rates of change; and
a plurality of signal managers interfacing with the analyzer element and the periodic set of components configured to exclude signals based on content properties of data transmitted;
wherein the plurality of components and the periodic set of components are configured to interface with a threat detector.
2 . The system of claim 1 , wherein the analyzer element comprises a threshold application component, a terrain updater, an outlier analysis module, a threshold violation predictor, a time-ordered behavior evaluator, and a graph updater.
3 . The system of claim 1 , wherein the periodic set of components comprises a peer to peer analyzer, an actor correlation analyzer, an actor behavior analyzer, a rate of change predictor, and a semantic rule analyzer.
4 . The system of claim 1 , wherein a first signal manager is provided with the analyzer element and a second signal manager is provided with the periodic set of components, and the first signal manger and the second signal manager interface with a signal filter configured to receive signal weights from a signal weight repository.
5 . The system of claim 1 wherein the threat detector employs an extreme vigilance application programming interface.
6 . The system of claim 1 , wherein the outlier analyzer determines whether or not frequency, periodicity, and general value of outliers implies the start of another data pattern or a change to an existing data pattern.
7 . The system of claim 2 , wherein time-ordered behavior evaluator employs a Markov Graph, to learn a general sequence of events performed by one actor during a time period.
8 . The system of claim 3 , wherein the actor behavior analyzer is configured to examine any changes in actor behavior over time by comparing similarity of past behavior with current behavior.
9 . The system of claim 3 , wherein the semantic rule analyzer is configured to encode conditional, provisional, cognitive, operational, and functional knowledge.
10 . The system of claim 3 , wherein the rate of change predictor is configured to store similarity and correlation results over time and rates of change over time.
11 . A system for performing cognitive modeling, comprising:
an event acquirer configured to acquire an event comprising an associated date and set of data fields;
an analyzer element comprising a plurality of components repeated for each field in an event received from the event acquirer;
a periodic set of components configured to operate periodically on demand to analyze and predict based on information received from the analyzer element; and
a plurality of signal managers interfacing with the analyzer element and the periodic set of components, wherein the periodic set of components is configured to exclude signals based on content properties of data transmitted;
wherein the plurality of components and the periodic set of components are configured to interface with a threat detector.
12 . The system of claim 11 , wherein the analyzer element comprises a threshold application component, a terrain updater, an outlier analysis module, a threshold violation predictor, a time-ordered behavior evaluator, and a graph updater.
13 . The system of claim 11 , wherein the periodic set of components comprises a peer to peer analyzer, an actor correlation analyzer, an actor behavior analyzer, a rate of change predictor, and a semantic rule analyzer.
14 . The system of claim 11 , wherein a first signal manager is provided with the analyzer element and a second signal manager is provided with the periodic set of components, and the first signal manger and the second signal manager interface with a signal filter configured to receive signal weights from a signal weight repository.
15 . The system of claim 11 wherein the threat detector employs an extreme vigilance application programming interface.
16 . The system of claim 11 , wherein the outlier analyzer determines whether or not frequency, periodicity, and general value of outliers implies the start of another data pattern or a change to an existing data pattern.
17 . The system of claim 12 , wherein time-ordered behavior evaluator employs a Markov Graph, to learn a general sequence of events performed by one actor during a time period.
18 . The system of claim 13 , wherein the actor behavior analyzer is configured to examine any changes in actor behavior over time by comparing similarity of past behavior with current behavior.
19 . A cognitive modeling apparatus, comprising:
an event acquirer;
an updating and evaluating arrangement comprising hardware configured to apply thresholds, update event related data, predict thresholds and determine outliers from events received from the event acquirer; and
a periodic/on demand apparatus configured to analyze event data on demand; and
a series of signal managers comprising a first signal manager connected to the updating and evaluation arrangement and a second signal manager connected to the periodic/on demand apparatus;
wherein the series of signal managers are configured to exclude signals based on content properties.
20 . The cognitive modeling apparatus of claim 19 , further comprising a threat detector configured to detect threats and a cognitive modeling vigilance apparatus.